Information from 1,500 households was extracted from a survey conducted in Sub-Saharan Africa. The data was collected using a structured questionnaire from randomly selected households. The main purpose of the survey was to evaluate the differences in household health expenditure after the implementation of financial inclusion training. The training was open for all male and female respondents residing in both rural and urban areas. Health expenditure is used as a measure of health and wellbeing within households, where increased health expenditure implies an improvement in health and well-being resulting according to the sustainable development goal 3 (SDG3). The area of study was chosen because financial inclusion for households within the area is considered low. This means that their ownership and use of financial products including financial technologies is low; they do not have adequate access to credit and receive little remittance. Helping them to improve on the level of financial inclusion means that households can now save more, have better access to credit, receive more remittances, and make use of modern financial technologies to make and receive payments. Improvement in household income resulting from improved financial inclusion can be spent on healthcare to improve health and wealth. The reverse is true when the household spends less on healthcare because of lower levels of financial inclusion or complete exclusion. The respondents were divided into two some were given financial inclusion training (treatment) and others were also not given financial inclusion training (control) so in the end, we compared the health expenditure levels between the two groups. The difference in health expenditure helps to determine the impact of the financial inclusion training. Other characteristics of the respondents are their household size, age, sex, employment status and location of the household. The descriptions of variables included in the information are provided in Table 1. 

Table 1

(a) Examine and evaluate the list of variables. Answer the following questions:

(i) What are the types of data covered in the above information?

(ii) Briefly discuss the characteristics of these types of data. 

(iii) What is the importance of understanding the different types of data? Calculate the mean, range and standard deviation for expenditure, household size, and age. Show your workings. Interpret the results.

 

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Table 1 Variable Expenditure Household Size Age Sex Training Notation X₁ X₂ Location X3 X₂ Xs Employment X6 status) X7 Description This is the total amount of household expenditure (in $) on various health-related issues. The total number of members of household living under the same roof and sharing same food. This is the age of the household head (in years) - the main decision maker within the household. This is the sex of the household head the main decision maker within the household. Codes values are in SexCode (1-Male; 0-Female) This is a categorical (binary) variable to indicate whether the household head attended the financial inclusion training or not, with values: Control these are the household heads who did not attend the financial inclusion training. Treatment these are the household heads who attended the financial inclusion training. Coded values: Training Code (1-Treatment; 0-Control) This is a categorical variable representing the employment status of the household head. The values are: Unemployed those who are considered unemployed. Retired/Inactive-those who are not unemployed but are currently not economically active Employee - those who are employed but working for someone. Self-employed those who are self-employed. Coded values: Empsta tCode (1=Unemployed; 2-Retired/Inactive; 3-Employee; 4-Self-employed) This is the location of household, whether they are living in rural or urban areas of the country. Coded values: 1-Rural; 0=Urban Table 1 Variable Expenditure Household Size Age Sex Training Notation X₁ X₂ Location X3 X₂ Xs Employment X6 status) X7 Description This is the total amount of household expenditure (in $) on various health-related issues. The total number of members of household living under the same roof and sharing same food. This is the age of the household head (in years) - the main decision maker within the household. This is the sex of the household head the main decision maker within the household. Codes values are in SexCode (1-Male; 0-Female) This is a categorical (binary) variable to indicate whether the household head attended the financial inclusion training or not, with values: Control these are the household heads who did not attend the financial inclusion training. Treatment these are the household heads who attended the financial inclusion training. Coded values: Training Code (1-Treatment; 0-Control) This is a categorical variable representing the employment status of the household head. The values are: Unemployed those who are considered unemployed. Retired/Inactive-those who are not unemployed but are currently not economically active Employee - those who are employed but working for someone. Self-employed those who are self-employed. Coded values: Empsta tCode (1=Unemployed; 2-Retired/Inactive; 3-Employee; 4-Self-employed) This is the location of household, whether they are living in rural or urban areas of the country. Coded values: 1-Rural; 0=Urban

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SOLUTION i The types of data covered in the above information are Expenditure This is continuous numerical data representing the total amount of household expenditure on healthrelated issues It is mea... View the full answer